Calculates optimum sample size and cut-point positives
to achieve specified population sensitivity, for
given population size and other parameters, all paramaters must be scalars

Usage

1

Arguments

N

population size

sep

target population sensitivity

c

The maximum allowed cut-point number of positives to classify a cluster
as positive, default=1, if positives < c result is negative, >= c is positive

se

test unit sensitivity

sp

test unit specificity, default=1

pstar

design prevalence as a proportion or integer (number of infected units)

minSpH

minimium desired population specificity

Value

a list of 3 elements, a dataframe with 1 row and six columns for
the recommended sample size and corresponding values for population sensitivity (SeP),
population specificity (SpP), N, c and pstar, a vector of SeP values
and a vector of SpP values, for n = 1:N